def eval_single(img,
model = None):
if type(img) == str:
img = cv2.imread(img)
if not model:
model = AgePredModel(eval_use_only=True)
int2gender = {0: 'Female', 1: 'Male'}
# input image
preds, rects, scores = model.getAgeGender(img,
transformed=False,
return_all_faces=True,
return_info=True)
gen_pred, age_pred = -1, -1
for pred, (x, y, w, h), score in zip(preds, rects, scores):
# model predictions
gen_pred, gen_prob, age_pred, age_var = pred
age_pred, gen_pred = float(age_pred), int(gen_pred)
age_var, gen_prob = int(age_var), float(gen_prob)
# vars
color = (255, 0, 0) if gen_pred == 1 else (0, 0, 255)
fontscale = min(1.5, max(0.3, max(w, h) / 500))
fill_h = int(35 * fontscale)
font_h = int(6 * fontscale)
thickness = 1 if fontscale <= 1 else 2
# draw a rectange to bound the face
cv2.rectangle(img, (x, y), (x + w, y + h), color, 4)
# fill an area with color for text show
cv2.rectangle(img, (x, y + h - fill_h), (x + w, y + h), color, cv2.FILLED)
# put text
font = cv2.FONT_HERSHEY_DUPLEX
cv2.putText(img,
"{:.0f}% {}, {:.0f} +/- {}".format(100 * gen_prob,
int2gender[gen_pred],
age_pred,
age_var),
org=(x + 6, y + h - font_h),
fontFace=font,
fontScale=fontscale,
color=(255, 255, 255),
thickness=thickness)
return img, gen_pred, age_pred
def eval_live():
cap = cv2.VideoCapture(0)
model = AgePredModel(eval_use_only=True)
while True:
# Capture frame-by-frame
ret, frame = cap.read()
# Our operations on the frame come here
labeled, _, _ = eval_single(frame, model)
# Display the resulting frame
cv2.imshow('frame', labeled)
if cv2.waitKey(1) & 0xFF == ord('q'):
break
# When everything done, release the capture
cap.release()
cv2.destroyAllWindows()
def evaluate(path, name_contain_label=False, result_path=None):
"""
function used to test a folder of images
:param path: folder path, e.g. config.val, last char should be '/'
:param name_contain_label: if set, label is extracted from image name
:param result_path: path to store the result, default path + "test_results/"
:return:
"""
# check param: path
if path[-1] != "/":
print("[WARNING] PARAM: path NOT ENDS WITH '/'!")
path += '/'
# check param: result_path
if result_path is None:
result_path = path + "test_results/"
# make sure it exists and is empty
if not os.path.exists(result_path):
os.mkdir(result_path)
clear_dir(result_path)
# start eval
model = AgePredModel(eval_use_only=True)
int2gender = {0: 'Female', 1: 'Male'}
for img_path in glob.glob(path + "*"):
# check image
img_name = img_path[len(path):]
formatt = re.findall("[^.]*.([^.]*)", img_name)[0]
if not formatt: continue
formatt = formatt.lower()
if not formatt in ['png', 'jpg', 'jpeg']: continue
print("[evaluate] Eval {} ...".format(img_name), end='')
# input image
preds, rects, scores = model.getAgeGender(img_path,
transformed=False,
return_all_faces=True,
return_info=True)
img = cv2.imread(img_path)
for (gender_pred, age_pred), (x, y, w,
h), score in zip(preds, rects, scores):
age_pred, gender_pred = float(age_pred), int(gender_pred)
# draw a rectange to bound the face
cv2.rectangle(img, (x, y), (x + w, y + h), (0, 0, 255), 4)
# fill an area with color for text show
color = (255, 0, 0) if gender_pred else (0, 0, 255)
cv2.rectangle(img, (x, y + h - 35), (x + w, y + h), color,
cv2.FILLED)
# put text
font = cv2.FONT_HERSHEY_DUPLEX
cv2.putText(img,
"{}, {:.0f}, {:.2f}".format(int2gender[gender_pred],
age_pred, score),
org=(x + 6, y + h - 6),
fontFace=font,
fontScale=1.0,
color=(255, 255, 255),
thickness=1)
# bottomLeftCornerOfText = (min(img.shape[1], x + 4), max(0, y - 12))
# if x < max(24., 0.05 * img.shape[0]):
# bottomLeftCornerOfText = (min(img.shape[1], x + 4), min(img.shape[1], y + h - 2))
# fontScale = 1
# fontColor = (255, 0, 0) if gender_pred else (0, 0, 255)
# lineType = 2
# cv2.putText(img,
# "{}, {:.0f}, {:.2f}".format(int2gender[gender_pred], age_pred, score),
# bottomLeftCornerOfText,
# font,
# fontScale,
# fontColor,
# lineType)
cv2.imwrite(result_path + img_name, img)
print(" Done!")
def eval_batch(path, model_name, name_contain_label=False, result_path=None):
"""
function used to test a folder of images
:param path: folder path, e.g. config.val, last char should be '/'
:param name_contain_label: if set, label is extracted from image name
:param result_path: path to store the result, default path + "test_results/"
:return:
"""
# check param: path
if path[-1] != "/":
print("[WARNING] PARAM: path NOT ENDS WITH '/'!")
path += '/'
# check param: result_path
if result_path is None:
result_path = path + "all_results/"
false_results = result_path + "false_results/"
all_results = result_path + "all_results/"
# make sure it exists and is empty
if not os.path.exists(result_path):
os.mkdir(result_path)
clear_dir(result_path)
if not os.path.exists(all_results):
os.mkdir(all_results)
# also the false preds samples if we know the label
if name_contain_label:
if not os.path.exists(false_results):
os.mkdir(false_results)
clear_dir(false_results)
# start eval
model = AgePredModel(eval_use_only=True, model_name=model_name)
for img_path in glob.glob(path + "*"):
# only load 'png', 'jpg', 'jpeg' images
img_name = img_path[len(path):]
formatt = re.findall("[^.]*.([^.]*)", img_name)[0]
if not formatt: continue
formatt = formatt.lower()
if not formatt in ['png', 'jpg', 'jpeg']: continue
# image qualified for eval
print("[evaluate] evaluating {}".format(img_name))
img = cv2.imread(img_path)
img, gen_pred, age_pred = eval_single(img, model)
# write the result
cv2.imwrite(all_results + img_name, img)
# if labeled
if name_contain_label:
try:
(age, gender) = re.findall(r'([^_]*)_([^_]*)_*', img_name)[0]
age, gender = int(age), int(gender)
if abs(age - age_pred) >= 5:
cv2.imwrite(false_results + img_name, img)
except:
print("Error while extracting labels from {}".format(img_name))
print("[evaluate] Done!")